The addition of Angela Eaton of Texas Tech University brings a fresh tone to her updates of content and pedagogy while retaining the authoritative voice of Carolyn Rude. Some of the text's changes include an update to Chapter 6, "Electronic Editing," and examples about editing Web sites are found throughout the text to support the increased role of online resources in every aspect of communication.

    This is the book that brought gender differences in ways of speaking to the forefront of public awareness. With a rare combination of scientific insight and delightful, humorous writing, Tannen shows why women and men can walk away from the same conversation with completely different impressions of what was said.Studded with lively and entertaining examples of real conversations, this book gives you the tools to understand what went wrong -- and to find a common language in which to strengthen relationships at work and at home. A classic in the field of interpersonal relations, this book will change forever the way you approach conversations.

    A guide for creating manuals, online help, and Web publications showing correct grammar, punctuation, and common misspellings of computer topics and terms.

    Never again will you order the Poisson Distribution in a French restaurant!This updated version features all new material.

    Often, computer science and computer engineering curricula don't provide students with a concentrated and consistent introduction to the fundamental concepts that underlie all computer systems. Traditional computer organization and logic design courses cover some of this material, but they focus largely on hardware design. They provide students with little or no understanding of how important software components operate, how application programs use systems, or how system attributes affect the performance and correctness of application programs. - A more complete view of systems - Takes a broader view of systems than traditional computer organization books, covering aspects of computer design, operating systems, compilers, and networking, provides students with the understanding of how programs run on real systems. - Systems presented from a programmers perspective - Material is presented in such a way that it has clear benefit to application programmers, students learn how to use this knowledge to improve program performance and reliability. They also become more effective in program debugging, because t

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Presentation Zen challenges the conventional wisdom of making "slide presentations" in today’s world and encourages you to think differently and more creatively about the preparation, design, and delivery of your presentations. Garr shares lessons and perspectives that draw upon practical advice from the fields of communication and business. Combining solid principles of design with the tenets of Zen simplicity, this book will help you along the path to simpler, more effective presentations.--back cover

    It explores the critical concepts while also examining why they are relevant. The core content is presented within the framework of predicting products, proposing mechanisms, and solving synthesis problems. Readers will fine-tune the key skills involved in solving those types of problems with the help of interactive, step-by-step instructions and problems.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Yet it is their good opinion you need to win if you hope to get ahead.Among the curmudgeon's day-to-day tips for the workplace:- Excise the word "like" from your spoken English - Don't suck up - Stop "reaching out" and "sharing" - Rid yourself of piercings, tattoos, and weird hair colors - Make strong language countHis larger career advice includes:- What to do if you have a bad boss - Coming to grips with the difference between being nice and being good - How to write when you don't know what to say - Being judgmental (it's good, and you don't have a choice anyway)And on the great topics of life, the curmudgeon urges us to leave home no matter what, get real jobs (not internships), put ourselves in scary situations, and watch Groundhog Day repeatedly (he'll explain).Witty, wise, and pulling no punches, The Curmudgeon's Guide to Getting Ahead is an indispensable sourcebook for living an adult life.

    This ninth edition covers both analytical and empirical approaches to the subject. The examples and templates provide students with resources for computer-numerical solutions.

    It is the best and most successful guide to reading comprehension for the general reader. And now it has been completely rewritten and updated. You are told about the various levels of reading and how to achieve them – from elementary reading, through systematic skimming and inspectional reading, to speed reading, you learn how to pigeonhole a book, X-ray it, extract the author's message, criticize. You are taught the different reading techniques for reading practical books, imaginative literature, plays, poetry, history, science and mathematics, philosophy and social science. Finally, the authors offer a recommended reading list and supply reading tests whereby you can measure your own progress in reading skills, comprehension and speed.This a previously-published edition of ISBN 9780671212094

    Through memorable visuals and honest talk, John Ruszkiewicz shows students how to write in any situation — wherever they are in their writing process.With everything you need to teach composition, the Guide lays out focused advice for writing common genres, while the Reference covers the range of writing and research skills that students need as they work across genres and disciplines. An intuitive, visual cross-referencing system and a modular chapter organization that’s simple to follow make it even easier for students to work back and forth between chapters and stay focused on their own writing.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa